Data Scientist, AWS Support Capacity Planning

Amazon; Dallas (TX); On-site; USD 136,000 - 184,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Job summary

AWS Applied AI Solutions (AAIS) in Dallas, Texas is seeking a skilled Data Scientist to model contact and volume forecasting and develop state-of-the-art AI-driven solutions that optimize the Support network.

You will work with data engineering, operations, and finance teams to build scalable forecasting and optimization models, applying ML and statistical techniques in a fast-paced environment. Opportunities include technical leadership and global impact.

Qualifications

• 2+ years of data scientist experience.
• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience.
• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience.
• Experience applying theoretical models in an applied environment.

Responsibilities

• Forecast contact and volume forecasting to drive business and operational improvements.
• Build forecasting, predictive, and optimization models.
• Collaborate with data engineering, tooling, operations, training, workforce management and finance teams.

Skills

Data science

SQL

Python

R

Tools

SAS

MATLAB

Job description

Description

AWS Applied AI Solutions (AAIS) is building toward a future where every business innovates with Amazon AI teammates. To get there, we build AI solutions that improve human capabilities and transform entire business functions. We create end-to-end products that surprise and delight out-of-the-box, making complex things easy and hard things possible, with no cloud experience required. We start with customers who embrace the future and build bridges to meet the rest where they are. We pursue ambitious opportunities with conviction, and we are looking for builders who share that mindset.

Do you have proven analytical capabilities to identify business opportunities, develop predictive models, and optimization algorithms to help us build state of the art Support organization?

At Amazon we are working to be the most customer-centric company on earth. To get there we need exceptionally talented bright and driven people. We set big goals and are looking for people who can help us reach and exceed them. Amazon Web Services (AWS) is one of the world's most comprehensive and broadly adopted cloud platform offering over 200 fully featured services from data centers globally. Amazon Web Services Inc. provides services for a broad range of applications including compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), security, and application development, deployment, and management.

AWS Support's Capacity Planning team is looking for a strong talented Data Scientist to model contact and volume forecasting discovering insights and identifying opportunities through the use of statistics machine learning and combinatorial optimization problems to drive business and operational improvements. You are passionate about building solutions that will help drive a more efficient operations network and optimize cost. In this role you will partner with data engineering tooling team operations training workforce management and finance teams driving optimization and prediction solutions across the network influencing the long-term strategy of the business.

We are looking for an experienced and motivated Data Scientist with proven abilities to build and manage modeling projects forecasting solutions identify data requirements build methodology and tools that are statistically grounded. You are an expert in the areas of data science forecasting optimization machine learning and statistics and are comfortable facilitating ideation and working from concept through execution. You are customer obsessed innovative independent results-oriented and enjoys working in a fast-paced growing organization. An interest in operations process improvement is helpful. The ability to embrace this ambiguity and work with a highly distributed team of experts is critical. While this is a small team there is opportunity to own globally impactful work and grow your career in technical programmatic or people leadership. You will likely work in Python or R building forecasting predictive and optimization models. Your problem solving ability knowledge of data models and ability to drive results through ambiguity are more important to us.

About Us

About the team

Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity and AmazeCon conferences, inspire us to never stop embracing our uniqueness.

We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Basic Qualifications

• 2+ years of data scientist experience

• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience

• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience

• Experience applying theoretical models in an applied environment

Preferred Qualifications

• Experience in Python, Perl, or another scripting language

• Experience in a ML or data scientist role with a large technology company

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits .

USA, TX, Dallas - 136,000.00 - 184,000.00 USD annually

USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually